my_model
This model is a fine-tuned version of FYP19/t5-small-finetuned-wikisql on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0809
- Rouge2 Precision: 0.8049
- Rouge2 Recall: 0.4562
- Rouge2 Fmeasure: 0.524
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
0.0458 | 1.0 | 916 | 0.0637 | 0.708 | 0.4014 | 0.4557 |
0.0266 | 2.0 | 1832 | 0.0644 | 0.7558 | 0.4234 | 0.4847 |
0.0206 | 3.0 | 2748 | 0.0676 | 0.7735 | 0.4395 | 0.5012 |
0.0163 | 4.0 | 3664 | 0.0695 | 0.765 | 0.4318 | 0.4932 |
0.0119 | 5.0 | 4580 | 0.0728 | 0.7956 | 0.452 | 0.5176 |
0.0099 | 6.0 | 5496 | 0.0755 | 0.7914 | 0.4452 | 0.5106 |
0.0069 | 7.0 | 6412 | 0.0790 | 0.7882 | 0.4421 | 0.5081 |
0.0052 | 8.0 | 7328 | 0.0809 | 0.8049 | 0.4562 | 0.524 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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